Fundamentals of digital image processing
Fundamentals of digital image processing
Classification of newspaper image blocks using texture analysis
Computer Vision, Graphics, and Image Processing
Text segmentation using Gabor filters for automatic document processing
Machine Vision and Applications - Special issue: document image analysis techniques
Document Representation and Its Application to Page Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Zone Classification Using Texture Features
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
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Page segmentation is one of the important stage in most document processing systems. Algorithms found in published literatures often rely on some predetermined parameters such as general font sizes, distances between text lines and document scan resolutions. Variations of these parameters in real document images greatly affect the performance of the algorithms. In this paper we present a novel approach for document page segmentation using dynamic local connectivity transform. An efficient implementation of a local connectivity algorithm transforms a document image into a parameter domain in which a parameter value at a pixel location represents a connectivity property for its neighboring foreground pixels in the original document image. Then a top-down approach with a linear search reveals the document regions at each resolution levels as text block, text lines and graphics. We consider our algorithm a transform based multi-resolution method. Our ongoing research shows that the algorithm is robust for variations of document parameters.